scholarly journals Evaluating the Reliability of Human Brain White Matter Tractometry

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
John Kruper ◽  
Jason D. Yeatman ◽  
Adam Richie-Halford ◽  
David Bloom ◽  
Mareike Grotheer ◽  
...  
Keyword(s):  
White Matter ◽  
Human Brain ◽  
High Reliability ◽  
Assessment Tools ◽  
Three Dimensions ◽  
Retest Reliability ◽  
Brain White Matter ◽  
Analysis Methods ◽  
Human Connectome Project ◽  
Test Retest Reliability

The validity of research results depends on the reliability of analysis methods. In recent years, there have been concerns about the validity of research that uses diffusion-weighted MRI (dMRI) to understand human brain white matter connections in vivo, in part based on the reliability of analysis methods used in this field. We defined and assessed three dimensions of reliability in dMRI-based tractometry, an analysis technique that assesses the physical properties of white matter pathways: (1) reproducibility, (2) test-retest reliability, and (3) robustness. To facilitate reproducibility, we provide software that automates tractometry (https://yeatmanlab.github.io/pyAFQ). In measurements from the Human Connectome Project, as well as clinical-grade measurements, we find that tractometry has high test-retest reliability that is comparable to most standardized clinical assessment tools. We find that tractometry is also robust: showing high reliability with different choices of analysis algorithms. Taken together, our results suggest that tractometry is a reliable approach to analysis of white matter connections. The overall approach taken here both demonstrates the specific trustworthiness of tractometry analysis and outlines what researchers can do to establish the reliability of computational analysis pipelines in neuroimaging.

scholarly journals Evaluating the reliability of human brain white matter tractometry

2021 ◽  
Author(s):  
John Kruper ◽  
Jason D. Yeatman ◽  
Adam Richie-Halford ◽  
David Bloom ◽  
Mareike Grotheer ◽  
...  
Keyword(s):  
White Matter ◽  
Human Brain ◽  
High Reliability ◽  
Assessment Tools ◽  
Three Dimensions ◽  
Retest Reliability ◽  
Brain White Matter ◽  
Analysis Methods ◽  
Human Connectome Project ◽  
Test Retest Reliability

The validity of research results depends on the reliability of analysis methods. In recent years, there have been concerns about the validity of research that uses diffusion-weighted MRI (dMRI) to understand human brain white matter connections in vivo, in part based on reliability of the analysis methods used in this field. We defined and assessed three dimensions of reliability in dMRI-based tractometry, an analysis technique that assesses the physical properties of white matter pathways: (1) reproducibility, (2) test-retest reliability and (3) robustness. To facilitate reproducibility, we provide software that automates tractometry (https://yeatmanlab.github.io/pyAFQ). In measurements from the Human Connectome Project, as well as clinical-grade measurements, we find that tractometry has high test-retest reliability that is comparable to most standardized clinical assessment tools. We find that tractometry is also robust: showing high reliability with different choices of analysis algorithms. Taken together, our results suggest that tractometry is a reliable approach to analysis of white matter connections. The overall approach taken here both demonstrates the specific trustworthiness of tractometry analysis and outlines what researchers can do to demonstrate the reliability of computational analysis pipelines in neuroimaging.

scholarly journals The Brain Metastases Symptom Checklist as a novel tool for symptom measurement in patients with brain metastases undergoing whole-brain radiotherapy

2016 ◽  
Vol 23 (3) ◽  
pp. 239 ◽  
Author(s):  
D. Rodin ◽  
B. Banihashemi ◽  
L. Wang ◽  
A. Lau ◽  
S. Harris ◽  
...  
Keyword(s):  
Brain Metastases ◽  
Intraclass Correlation ◽  
Whole Brain Radiotherapy ◽  
Assessment Tools ◽  
Symptom Checklist ◽  
Retest Reliability ◽  
Brain Radiotherapy ◽  
Test Retest Reliability ◽  
The Brain ◽  
Responsiveness To Change

Purpose We evaluated the feasibility, reliability, and validity of the Brain Metastases Symptom Checklist (BMSC), a novel self-report measure of common symptoms experienced by patients with brain metastases.Methods Patients with first-presentation symptomatic brain metastases (n = 137) referred for whole-brain radiotherapy (WBRT) completed the BMSC at time points before and after treatment. Their caregivers (n = 48) provided proxy ratings twice on the day of consultation to assess reliability, and at week 4 after WBRT to assess responsiveness to change. Correlations with 4 other validated assessment tools were evaluated.Results The symptoms reported on the BMSC were largely mild to moderate, with tiredness (71%) and difficulties with balance (61%) reported most commonly at baseline. Test–retest reliability for individual symptoms had a median intraclass correlation of 0.59 (range: 0.23–0.85). Caregiver proxy and patient responses had a median intraclass correlation of 0.52. Correlation of absolute scores on the BMSC and other symptom assessment tools was low, but consistency in the direction of symptom change was observed. At week 4, change in symptoms was variable, with improvements in weight gain and sleep of 42% and 41% respectively, and worsening of tiredness and drowsiness of 62% and 59% respectively.Conclusions The BMSC captures a wide range of symptoms experienced by patients with brain metastases, and it is sensitive to change. It demonstrated adequate test–retest reliability and face validity in terms of its responsiveness to change. Future research is needed to determine whether modifications to the BMSC itself or correlation with more symptom-specific measures will enhance validity. 

scholarly journals Psychometric properties of gross motor assessment tools for children: a systematic review

BMJ Open ◽  
2018 ◽  
Vol 8 (10) ◽  
pp. e021734 ◽  
Author(s):  
Alison Griffiths ◽  
Rachel Toovey ◽  
Prue E Morgan ◽  
Alicia J Spittle
Keyword(s):  
Psychometric Properties ◽  
Predictive Validity ◽  
Methodological Quality ◽  
Clinical Utility ◽  
Assessment Tools ◽  
Motor Assessment ◽  
Gross Motor ◽  
Retest Reliability ◽  
Validity Test ◽  
Test Retest Reliability

ObjectiveGross motor assessment tools have a critical role in identifying, diagnosing and evaluating motor difficulties in childhood. The objective of this review was to systematically evaluate the psychometric properties and clinical utility of gross motor assessment tools for children aged 2–12 years.MethodA systematic search of MEDLINE, Embase, CINAHL and AMED was performed between May and July 2017. Methodological quality was assessed with the COnsensus-based Standards for the selection of health status Measurement INstruments checklist and an outcome measures rating form was used to evaluate reliability, validity and clinical utility of assessment tools.ResultsSeven assessment tools from 37 studies/manuals met the inclusion criteria: Bayley Scale of Infant and Toddler Development-III (Bayley-III), Bruininks-Oseretsky Test of Motor Proficiency-2 (BOT-2), Movement Assessment Battery for Children-2 (MABC-2), McCarron Assessment of Neuromuscular Development (MAND), Neurological Sensory Motor Developmental Assessment (NSMDA), Peabody Developmental Motor Scales-2 (PDMS-2) and Test of Gross Motor Development-2 (TGMD-2). Methodological quality varied from poor to excellent. Validity and internal consistency varied from fair to excellent (α=0.5–0.99). The Bayley-III, NSMDA and MABC-2 have evidence of predictive validity. Test–retest reliability is excellent in the BOT-2 (intraclass correlation coefficient (ICC)=0.80–0.99), PDMS-2 (ICC=0.97), MABC-2 (ICC=0.83–0.96) and TGMD-2 (ICC=0.81–0.92). TGMD-2 has the highest inter-rater (ICC=0.88–0.93) and intrarater reliability (ICC=0.92–0.99).ConclusionsThe majority of gross motor assessments for children have good-excellent validity. Test–retest reliability is highest in the BOT-2, MABC-2, PDMS-2 and TGMD-2. The Bayley-III has the best predictive validity at 2 years of age for later motor outcome. None of the assessment tools demonstrate good evaluative validity. Further research on evaluative gross motor assessment tools are urgently needed.

scholarly journals Computerized Symbol Digit Modalities Test in a Swiss Pediatric Cohort Part 1: Validation

2021 ◽  
Vol 12 ◽  
Author(s):  
Céline Hochstrasser ◽  
Sarah Rieder ◽  
Ursina Jufer-Riedi ◽  
Marie-Noëlle Klein ◽  
Anthony Feinstein ◽  
...  
Keyword(s):  
High Reliability ◽  
Age Groups ◽  
Reliable Change Index ◽  
Information Processing Speed ◽  
Retest Reliability ◽  
Norm Values ◽  
Significant Difference ◽  
Test Retest Reliability ◽  
The University ◽  
Mean Time

ObjectiveThe objective of this study was to validate the computerized Symbol Digit Modalities Test (c-SDMT) in a Swiss pediatric cohort, in comparing the Swiss sample to the Canadian norms. Secondly, we evaluated sex effects, age-effects, and test–retest reliability of the c-SDMT in comparison to values obtained for the paper and pencil version of the Symbol Digit Modalities Test (SDMT).MethodsThis longitudinal observational study was conducted in a single-center setting at the University Children’s Hospital of Bern. Our cohort consisted of 86 children (45 male and 41 female) aged from 8 to 16 years. The cohort included both healthy participants (n = 38) and patients (n = 48) hospitalized for a non-neurological disease. Forty eight participants were assessed during two testing sessions with the SDMT and the c-SDMT.ResultsTest–retest reliability was high in both tests (SDMT: ICC = 0.89, c-SDMT: ICC = 0.90). A reliable change index was calculated for the SDMT (RCIp = −3.18, 14.01) and the c-SDMT (RCIp = −5.45, 1.46) corrected for practice effects. While a significant age effect on information processing speed was observed, no such effect was found for sex. When data on the c-SDMT performance of the Swiss cohort was compared with that from a Canadian cohort, no significant difference was found for the mean time per trial in any age group. Norm values for age groups between 8 and 16 years in the Swiss cohort were established.ConclusionNorms for the c-SDMT between the Swiss and the Canadian cohort were comparable. The c-SDMT is a valid alternative to the SDMT. It is a feasible and easy to administer bedside tool due to high reliability and the lack of motor demands.

Real-Time Ex-Vivo Magnetic Resonance Image—Guided Dissection of Human Brain White Matter: A Proof-of-Principle Study

2019 ◽  
Vol 125 ◽  
pp. 198-206 ◽  
Author(s):  
Giacomo Bertolini ◽  
Emanuele La Corte ◽  
Domenico Aquino ◽  
Elena Greco ◽  
Zefferino Rossini ◽  
...  
Keyword(s):  
White Matter ◽  
Magnetic Resonance ◽  
Human Brain ◽  
Real Time ◽  
Magnetic Resonance Image ◽  
Ex Vivo ◽  
Image Guided ◽  
Brain White Matter ◽  
Proof Of Principle

scholarly journals Test-Retest Reliability of Diffusion Measures Extracted Along White Matter Language Fiber Bundles Using HARDI-Based Tractography

2019 ◽  
Vol 12 ◽  
Author(s):  
Mariem Boukadi ◽  
Karine Marcotte ◽  
Christophe Bedetti ◽  
Jean-Christophe Houde ◽  
Alex Desautels ◽  
...  
Keyword(s):  
White Matter ◽  
Fiber Bundles ◽  
Retest Reliability ◽  
Test Retest Reliability

Characterization of Myelin Fractions from Human Brain White Matter

1985 ◽  
Vol 44 (5) ◽  
pp. 1411-1418 ◽  
Author(s):  
Tony F. Cruz ◽  
Mario A. Moscarello
Keyword(s):  
White Matter ◽  
Human Brain ◽  
Brain White Matter

Microstructural Hyperelastic Characterization of Brain White Matter in Tension

2019 ◽  
Author(s):  
Mohammadreza Ramzanpour ◽  
Mohammad Hosseini-Farid ◽  
Mariusz Ziejewski ◽  
Ghodrat Karami
Keyword(s):  
Finite Element ◽  
White Matter ◽  
Human Brain ◽  
Volume Fraction ◽  
Fibrous Composite ◽  
Diffuse Axonal Injury ◽  
Stiffness Ratio ◽  
Fibrous Composite Material ◽  
Brain White Matter ◽  
The Brain

Abstract Axons as microstructural constituent elements of brain white matter are highly oriented in extracellular matrix (ECM) in one direction. Therefore, it is possible to model the human brain white matter as a unidirectional fibrous composite material. A micromechanical finite element model of the brain white matter is developed to indirectly measure the brain white matter constituents’ properties including axon and ECM under tensile loading. Experimental tension test on corona radiata conducted by Budday et al. 2017 [1] is used in this study and one-term Ogden hyperelastic constitutive model is applied to characterize its behavior. By the application of genetic algorithm (GA) as a black box optimization method, the Ogden hyperelastic parameters of axon and ECM minimizing the error between numerical finite element simulation and experimental results are measured. Inverse analysis is conducted on the resultant optimized parameters shows high correlation of coefficient (>99%) between the numerical and experimental data which verifies the accuracy of the optimization procedure. The volume fraction of axons in porcine brain white matter is taken to be 52.7% and the stiffness ratio of axon to ECM is perceived to be 3.0. As these values are not accurately known for human brain white matter, we study the material properties of axon and ECM for different stiffness ratio and axon volume fraction values. The results of this study helps to better understand the micromechanical structure of the brain and micro-level injuries such as diffuse axonal injury.

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